Abstract: In this paper, we propose a Connect6 solver which
adopts a hybrid approach based on a tree-search algorithm and image
processing techniques. The solver must deal with the complicated
computation and provide high performance in order to make real-time
decisions. The proposed approach enables the solver to be
implemented on a single Spartan-6 XC6SLX45 FPGA produced by
XILINX without using any external devices. The compact
implementation is achieved through image processing techniques to
optimize a tree-search algorithm of the Connect6 game. The tree
search is widely used in computer games and the optimal search brings
the best move in every turn of a computer game. Thus, many
tree-search algorithms such as Minimax algorithm and artificial
intelligence approaches have been widely proposed in this field.
However, there is one fundamental problem in this area; the
computation time increases rapidly in response to the growth of the
game tree. It means the larger the game tree is, the bigger the circuit
size is because of their highly parallel computation characteristics.
Here, this paper aims to reduce the size of a Connect6 game tree using
image processing techniques and its position symmetric property. The
proposed solver is composed of four computational modules: a
two-dimensional checkmate strategy checker, a template matching
module, a skilful-line predictor, and a next-move selector. These
modules work well together in selecting next moves from some
candidates and the total amount of their circuits is small. The details of
the hardware design for an FPGA implementation are described and
the performance of this design is also shown in this paper.
Abstract: Lateral-torsional buckling (LTB) is one of the
phenomenae controlling the ultimate bending strength of steel Ibeams
carrying distributed loads on top flange. Built-up I-sections
are used as main beams and distributors. This study investigates the
ultimate bending strength of such beams with sections of different
classes including slender elements. The nominal strengths of the
selected beams are calculated for different unsupported lengths
according to the Provisions of the American Institute of Steel
Constructions (AISC-LRFD). These calculations are compared with
results of a nonlinear inelastic study using accurate FE model for this
type of loading. The goal is to investigate the performance of the
provisions for the selected sections. Continuous distributed load at
the top flange of the beams was applied at the FE model.
Imperfections of different values are implemented to the FE model to
examine their effect on the LTB of beams at failure, and hence, their
effect on the ultimate strength of beams. The study also introduces a
procedure for evaluating the performance of the provisions compared
with the accurate FEA results of the selected sections. A simplified
design procedure is given and recommendations for future code
updates are made.
Abstract: Hierarchical classification is a problem with applications in many areas as protein function prediction where the dates are hierarchically structured. Therefore, it is necessary the development of algorithms able to induce hierarchical classification models. This paper presents experimenters using the algorithm for hierarchical classification called Multi-label Hierarchical Classification using a Competitive Neural Network (MHC-CNN). It was tested in ten datasets the Gene Ontology (GO) Cellular Component Domain. The results are compared with the Clus-HMC and Clus-HSC using the hF-Measure.
Abstract: Detection of player identity is challenging task in sport video content analysis. In case of soccer video player number recognition is effective and precise solution. Jersey numbers can be considered as scene text and difficulties in localization and recognition appear due to variations in orientation, size, illumination, motion etc. This paper proposed new method for player number localization and recognition. By observing hue, saturation and value for 50 different jersey examples we noticed that most often combination of low and high saturated pixels is used to separate number and jersey region. Image segmentation method based on this observation is introduced. Then, novel method for player number localization based on internal contours is proposed. False number candidates are filtered using area and aspect ratio. Before OCR processing extracted numbers are enhanced using image smoothing and rotation normalization.
Abstract: In this work, the results of mixing study by a jet mixer in a tank have been investigated in the laboratory scale. The tank dimensions are H/D=1 and the jet entrance have been considered in
the center of upper surface of tank. RNG-k-ε model is used as the
turbulent model for the prediction of the pattern of turbulent flow
inside the tank. For this purpose, a tank with volume of 110 liter is
simulated and it has been divided into 410,000 tetrahedral control
cells for performing the calculations. The grids at the vicinity of the
nozzle and suction pare are finer to get more accurate results. The
experimental results showed that in a vertical jet, the lowest mixing
time takes place at 35 degree. In addition, mixing time decreased by
increasing the Reynolds number. Furthermore, the CFD simulation
predicted the items as well a flow patterns precisely that validates the
experiments.
Abstract: This study investigates the performance of radial basis function networks (RBFN) in forecasting the monthly CO2 emissions of an electric power utility. We also propose a method for input variable selection. This method is based on identifying the general relationships between groups of input candidates and the output. The effect that each input has on the forecasting error is examined by removing all inputs except the variable to be investigated from its group, calculating the networks parameter and performing the forecast. Finally, the new forecasting error is compared with the reference model. Eight input variables were identified as the most relevant, which is significantly less than our reference model with 30 input variables. The simulation results demonstrate that the model with the 8 inputs selected using the method introduced in this study performs as accurate as the reference model, while also being the most parsimonious.
Abstract: Opportunistic Data Forwarding (ODF) has drawn much attention in mobile adhoc networking research in recent years. The effectiveness of ODF in MANET depends on a suitable routing protocol which provides a powerful source routing services. PLSR is featured by source routing, loop free and small routing overhead. The update messages in PLSR are integrated into a tree structure and no need to time stamp routing updates which reduces the routing overhead.
Abstract: The aim of this research is to determine how preservice Turkish teachers perceive themselves in terms of problem solving skills. Students attending Department of Turkish Language Teaching of Gazi University Education Faculty in 2005-2006 academic year constitute the study group (n= 270) of this research in which survey model was utilized. Data were obtained by Problem Solving Inventory developed by Heppner & Peterson and Personal Information Form. Within the settings of this research, Cronbach Alpha reliability coefficient of the scale was found as .87. Besides, reliability coefficient obtained by split-half technique which splits odd and even numbered items of the scale was found as r=.81 (Split- Half Reliability). The findings of the research revealed that preservice Turkish teachers were sufficiently qualified on the subject of problem solving skills and statistical significance was found in favor of male candidates in terms of “gender" variable. According to the “grade" variable, statistical significance was found in favor of 4th graders.
Abstract: Trends in business intelligence, e-commerce and
remote access make it necessary and practical to store data in
different ways on multiple systems with different operating systems.
As business evolve and grow, they require efficient computerized
solution to perform data update and to access data from diverse
enterprise business applications. The objective of this paper is to
demonstrate the capability of DTS [1] as a database solution for
automatic data transfer and update in solving business problem. This
DTS package is developed for the sales of variety of plants and
eventually expanded into commercial supply and landscaping
business. Dimension data modeling is used in DTS package to
extract, transform and load data from heterogeneous database
systems such as MySQL, Microsoft Access and Oracle that
consolidates into a Data Mart residing in SQL Server. Hence, the
data transfer from various databases is scheduled to run automatically
every quarter of the year to review the efficient sales analysis.
Therefore, DTS is absolutely an attractive solution for automatic data
transfer and update which meeting today-s business needs.
Abstract: This paper presents a robust vehicle detection approach using Haar-like feature. It is possible to get a strong edge feature from this Haar-like feature. Therefore it is very effective to remove the shadow of a vehicle on the road. And we can detect the boundary of vehicles accurately. In the paper, the vehicle detection algorithm can be divided into two main steps. One is hypothesis generation, and the other is hypothesis verification. In the first step, it determines vehicle candidates using features such as a shadow, intensity, and vertical edge. And in the second step, it determines whether the candidate is a vehicle or not by using the symmetry of vehicle edge features. In this research, we can get the detection rate over 15 frames per second on our embedded system.
Abstract: The determination of sugars in foods is very
significant. Their relation in fact, can affect the chemical and
sensorial quality of the matrix (e.g., sweetness, pH, total acidity,
microbial stability, global acceptability) and can provide information
on food to optimize several selected technological processes. Three
stages of ripeness (green, yellow and red) of tomatoes (Lycopersicon
Esculentum cv. Elegance) at different harvest dates were evaluated.
Fruit from all harvests were exposed to different of ozone doses
(0.25, 0.50 and 1 mg O3/g tomatoes) and clean air for 5 day at 15
°C±2 and 90-95 % relative humidity. Then, fruits were submitted for
extraction and analysis after a day from the finish of exposure of each
stage. The concentrations of the glucose and fructose increased in the
tomatoes which were subjected to ozone treatments.
Abstract: This paper presents Qmulus- a Cloud Based GPS
Model. Qmulus is designed to compute the best possible route which
would lead the driver to the specified destination in the shortest time
while taking into account real-time constraints. Intelligence
incorporated to Qmulus-s design makes it capable of generating and
assigning priorities to a list of optimal routes through customizable
dynamic updates. The goal of this design is to minimize travel and
cost overheads, maintain reliability and consistency, and implement
scalability and flexibility. The model proposed focuses on
reducing the bridge between a Client Application and a Cloud
service so as to render seamless operations. Qmulus-s system
model is closely integrated and its concept has the potential to be
extended into several other integrated applications making it capable
of adapting to different media and resources.
Abstract: Home is important for Chinese people. Because the
information regarding the house attributes and surrounding
environments is incomplete in most real estate agency, most house
buyers are difficult to consider the overall factors effectively and only
can search candidates by sorting-based approach. This study aims to
develop a decision support system for housing purchasing, in which
surrounding facilities of each house are quantified. Then, all
considered house factors and customer preferences are incorporated
into Simple Multi-Attribute Ranking Technique (SMART) to support
the housing evaluation. To evaluate the validity of proposed approach,
an empirical study was conducted from a real estate agency. Based on
the customer requirement and preferences, the proposed approach can
identify better candidate house with consider the overall house
attributes and surrounding facilities.
Abstract: Sowing date and density are two important factors in
produce of coriander. A field experiment was conducted with
treatments: sowing time (5 May, 20 May, 4 June and 19 June 2009)
and plant density (10, 30, 50 and 70 plants m-2). The experimental
plots were laid out in a factorial according to a RCBD with three
replications. Results showed that the effect of sowing dates and
densities were significant on grain yield and yield components, but
interaction effects between sowing time and density were non
significant for all of traits in this trial. At sowing times 5 May, 20
May, 4 June and 19 June, grain yield obtained 736.9, 837.8, 1003.1
and 1299.6 kg ha-1, respectively. At 10, 30, 50 and 70 plants m-2,
grain yield were 794.9, 1031.0, 1092.3 and 959.3 kg ha-1,
respectively. In this experiment, sowing at 19 June and 50 and 30
plants m-2 had the most grain yield.
Abstract: Modeling the behavior of the dialogue management in
the design of a spoken dialogue system using statistical methodologies
is currently a growing research area. This paper presents a work
on developing an adaptive learning approach to optimize dialogue
strategy. At the core of our system is a method formalizing dialogue
management as a sequential decision making under uncertainty whose
underlying probabilistic structure has a Markov Chain. Researchers
have mostly focused on model-free algorithms for automating the
design of dialogue management using machine learning techniques
such as reinforcement learning. But in model-free algorithms there
exist a dilemma in engaging the type of exploration versus exploitation.
Hence we present a model-based online policy learning
algorithm using interconnected learning automata for optimizing
dialogue strategy. The proposed algorithm is capable of deriving
an optimal policy that prescribes what action should be taken in
various states of conversation so as to maximize the expected total
reward to attain the goal and incorporates good exploration and
exploitation in its updates to improve the naturalness of humancomputer
interaction. We test the proposed approach using the most
sophisticated evaluation framework PARADISE for accessing to the
railway information system.
Abstract: The charnockitic and associated granitic rocks of Akure area were studied for their field and petrographic relationship's. The outcrops locations were plotted in Surfer 8. The granitic rock exhibits a porphyritic texture and outcrops in the north-eastern side of the study area while the charnockitics outcrop in the central/western part. An essentially dark coloured and fine grained intrusive exhibiting xenoliths and xenocrysts (plagioclase phenocrysts) of the granite outcrops between the granitic and charnockitic rocks. Mineralogically, the central rock combines the content of the other two indicating that it is most likely a product of their hybridization. The charnockitic magma is believed to have intruded and assimilated the granite substantially thereby contaminating itself and consequently emplacing the hybrid. The presented model of emplacement elucidates the hybridization proposal. Conclusively, the charnockitics are believed to be (a) younger than the granite, (b) of Pan-African age and (c) of igneous origin.
Abstract: A Decision Support System/Expert System for stock
portfolio selection presented where at first step, both technical and
fundamental data used to estimate technical and fundamental return
and risk (1st phase); Then, the estimated values are aggregated with
the investor preferences (2nd phase) to produce convenient stock
portfolio.
In the 1st phase, there are two expert systems, each of which is
responsible for technical or fundamental estimation. In the technical
expert system, for each stock, twenty seven candidates are identified
and with using rough sets-based clustering method (RC) the effective
variables have been selected. Next, for each stock two fuzzy rulebases
are developed with fuzzy C-Mean method and Takai-Sugeno-
Kang (TSK) approach; one for return estimation and the other for
risk. Thereafter, the parameters of the rule-bases are tuned with backpropagation
method. In parallel, for fundamental expert systems,
fuzzy rule-bases have been identified in the form of “IF-THEN" rules
through brainstorming with the stock market experts and the input
data have been derived from financial statements; as a result two
fuzzy rule-bases have been generated for all the stocks, one for return
and the other for risk.
In the 2nd phase, user preferences represented by four criteria and
are obtained by questionnaire. Using an expert system, four estimated
values of return and risk have been aggregated with the respective
values of user preference. At last, a fuzzy rule base having four rules,
treats these values and produce a ranking score for each stock which
will lead to a satisfactory portfolio for the user.
The stocks of six manufacturing companies and the period of
2003-2006 selected for data gathering.
Abstract: Bladder carcinoma is an important worldwide health problem. Both cystoscopy and urine cytology used in detecting bladder cancer suffer from drawbacks where cystoscopy is an invasive method and urine cytology shows low sensitivity in low grade tumors. This study validates easier and less time-consuming techniques to evaluate the value of combined use of angiogenin and clusterin in comparison and combination with voided urine cytology in the detection of bladder cancer patients. This study includes malignant (bladder cancer patients, n= 50), benign (n=20) and healthy (n=20) groups. The studied groups were subjected to cystoscopic examination, detection of bilharzial antibodies, urine cytology, and estimation of urinary angiogenin and clusterin by ELISA. The overall sensitivity and specificity were 66% and 75% for angiogenin, 70% and 82.5% for clusterin and 46% and 80% for voided urine cytology. Combined sensitivity of angiogenin and clusterin with urine cytology increased from 82 to 88%.
Abstract: The householder RLS (HRLS) algorithm is an O(N2)
algorithm which recursively updates an arbitrary square-root of the
input data correlation matrix and naturally provides the LS weight
vector. A data dependent householder matrix is applied for such
an update. In this paper a recursive estimate of the eigenvalue
spread and misalignment of the algorithm is presented at a very low
computational cost. Misalignment is found to be highly sensitive to
the eigenvalue spread of input signals, output noise of the system and
exponential window. Simulation results show noticeable degradation
in the misalignment by increase in eigenvalue spread as well as
system-s output noise, while exponential window was kept constant.
Abstract: This article presents the evolution and technological changes implemented on the full scale simulators developed by the Simulation Department of the Instituto de Investigaciones Eléctricas1 (Mexican Electric Research Institute) and located at different training centers around the Mexican territory, and allows US to know the last updates, basically from the input/output view point, of the current simulators at some facilities of the electrical sector as well as the compatible industry of the electrical manufactures and industries such as Comision Federal de Electricidad (CFE*, The utility Mexican company). Tendencies of these developments and impact within the operators- scope are also presented.